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Study Finds Corporate Data in Greenhouse Gas Emissions Riddled With Math Errors

By:
Chris Gaetano
Published Date:
Jan 12, 2022
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A recent study has found that, despite announced efforts to curb greenhouse gas emissions, certain companies are reporting data that literally does not add up, Accounting Today reported. Specifically, when checking the math in these emissions reports, the researchers— Andreas Hoepner, a professor at the University College Dublin’s Smurfit Graduate Business School, and and his colleague, Sergio Vega; Joeri Rogelj, director of research at the Grantham Institute at the Centre for Environmental Policy at Imperial College London; and Frank Schiemann, a professor of accounting at the University of Hamburg’s School of Business, Economics and Social Sciences—found numerous instances of errors, omissions and rounding issues (often down rather than up).

The study used data from the nonprofit Climate Disclosure Project, which provides reported figures on gross emissions and then breaks them down into as many as five categories, including business lines, region and type of greenhouse gas. The report found that, overall, about 30 percent of companies that report such information will have some sort of mathematical miscalculation in at least one of these categories in a given year. When looking only at oil and gas companies, that number jumps to 39 percent. 

For instance, ExxonMobil Corp. reported a total of 120 million tons of carbon dioxide emissions overall in 2016, but when the numbers were broken down by type, the total added up to 128 million. (ExxonMobil said that it report certain emissions separately.) Canada's Imperial Oil, meanwhile, reported 10.7 million tons of greenhouse gas emissions in 2014 ,but the sum, when accounting for the company's different business lines, was 50.7 million, five times the total number reported. This mismatch was so big that the researchers speculated it may have even been a typo. A spokesperson from Imperial declined to comment. 

While the report did not outright accuse these companies of manipulating the data, the researchers did say that the discrepancies are too in inconsistent to be the result of simple rounding errors. If they were, one would expect regular mismatches that are equally spread between negative and positive mismatches.